Medical image processing apparatus, medical image processing method

ABSTRACT

From a plurality of medical images in time phases, a target site is extracted t least one medical image, a reference point is set on each of a target-site side, and a periphery side of the target site which are on across from each other over an outline of the extracted target site, and movement information for the reference points is calculated.

TECHNICAL FIELD

The present invention relates to a medical image processing technique.

BACKGROUND ART

At a medical site, an image of a patient is captured by a medicalimaging apparatus such as an X-ray CT (Computed Tomography) apparatus,an MRI (Magnetic Resonance Imaging) apparatus, or a PET (PositionEmission Tomography) apparatus. By viewing the captured medical image indetail, an anatomical structure of various types of targetsites((organs) in the body of the patient and functional informationtherefor are obtained, and the information is used in diagnosis andtreatment.

Within the various types of target sites that comprise in a human body,there is a type of organ that moves with respect to target sites in theperiphery thereof. For example, the lungs move in accordance withrespiratory movement, and the heart moves to cause the circulation ofblood in a body. Even for the same target site, it is known that due toits structure or the presence absence of a lesion, movement (a directionof a movement or an amount of a movement) relative to the peripherydiffers depending on a position in the target site or on its surface(hereinafter, referred to as a position-within-target-site).

There is a demand from users (a doctor or the like) to be able torecognize a position-within-target-site having an abnormal movement todiscover a lesion, by visualizing, from medical images, differences inthe direction of a movement at the position-within-target-site that ismade to be a target, or in the amount of the movement (hereinafter,referred to as movement information). For example, there is a demand tobe able to specify an adhesion position in a surface of a lung frommedical images by visualizing differences in movement informationaccording to respiratory movement of a lung, with respect to differencesin position on the surface of the lung. In Japanese Patent Laid-Open No.2012-213604, a technique of specifying a lesion portion from a medicalimage, and calculating a level of infiltration to the periphery of thelesion portion from relative movement information of the lesion portionand peripheral portions thereof is disclosed.

However, in the technique recited in Japanese Patent Laid-Open No.2012-213604, it is not possible to visualize a difference in movementinformation in a difference in position in the lesion portion. In otherwords, even if this is applied, replacing the lesion portion recited inJapanese Patent Laid-Open No. 2012-213604 with a target site, it is notpossible to visualize differences in movement information in differencesin position-within-target-site for the target site, and the user is notable to recognize a position-within-target-site that has abnormalmovement information in the target site.

SUMMARY OF INVENTION

The present invention was conceived in view of these kinds of problems,and provides a technique for calculating information indicating arelative movement amount with respect to the periphery in eachposition-within-target-site of a target site, associating it with eachposition-within-target-site of the target site and then presenting theinformation.

According to a first aspect of the present invention, there is provideda medical image processing apparatus comprising:

acquisition means for acquiring a plurality of medical images in timephases;

extraction means for extracting a target site from at least one medicalimage from the plurality of medical images;

setting means for setting a reference point on each of a target-siteside, and a periphery side of the target site which are on across fromeach other over an outline of the target site extracted by theextraction means; and

calculation means for calculating movement information for the referencepoints set by the setting means.

According to a second aspect of the present invention, there is provideda medical image processing apparatus comprising:

acquisition means for acquiring plural pieces of medical image data intime phases;

extraction means for extracting a target site with respect to at leastone piece of the plural pieces of medical image data acquired inaccordance with the acquisition means;

setting means for respectively setting a reference point on an outlineof the target site extracted by the extraction means, and setting areference point on either a target-site side or a periphery side of thetarget site; and

movement information calculation means for calculating movementinformation for the reference points set by the setting means.

According to a third aspect of the present invention, there is provideda medical image processing method comprising:

an acquisition step for acquiring a plurality of medical ages in timephases;

an extraction step for extracting a target site from at least onemedical image from the plurality of medical images;

a setting step for setting a reference point on each of a target-siteside, and a periphery side of the target site which are across from eachother over an outline of the target site extracted in the extractionstep; and

a calculation step for calculating movement information for thereference points set in the setting step.

According to a fourth aspect of the present invention, there is provideda medical image processing method comprising:

an acquisition step for acquiring plural pieces of medical image data intime phases;

an extraction step for extracting a target site with respect to at leastone piece of the plural pieces of medical image data acquired inaccordance with the acquisition step;

a setting step for respectively setting a reference point on an outlineof the target site extracted in the extraction step, and setting areference point on either a target-site side or a periphery side of thetarget site; and

a movement information calculation step for calculating movementinformation for the reference points set in the setting step.

According to a fifth aspect of the present invention, there is provideda computer program for causing a computer to function as:

acquisition means for acquiring a plurality of medical images in timephases;

extraction means for extracting a target site from at least one medicalimage from the plurality of medical images;

setting means for setting a reference point on each of a target-siteside, and a periphery side of the target site which are on across fromeach other over an outline of the target site extracted by theextraction means; and

calculation means for calculating movement information for the referencepoints set by the setting means.

Further features of the present invention will became apparent from thefollowing description of exemplary embodiments (with reference to theattached drawings).

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram for illustrating an example configuration of amedical image processing system,

FIG. 2 is a flowchart of processing that a medical image processingapparatus 10 performs.

FIG. 3A is a view explaining a reference point setting method accordingto a reference point setting unit 43.

FIG. 3B is a view explaining a reference point setting method accordingto a reference point setting unit 43.

FIG. 3C is a view explaining a reference point setting method accordingto a reference point setting unit 43.

FIG. 4A is a view explaining processing in step S205.

FIG. 4B is a view explaining processing in step S205.

FIG. 5 is a view explaining a test result.

FIG. 6A is a view in which a method of a first embodiment has been usedon a pre-operation X-ray 4D-CT image to visualize a slippage.

FIG. 6B is a view in which a method of a first embodiment has been usedon pre-operation X-ray 4D-CT image to visualize a slippage.

FIG. 7A is a view explaining a first variation.

FIG. 7B is a view explaining a first variation.

FIG. 7C is a view explaining a first variation,

FIG. 7D is a view explaining a first variation.

FIG. 8 is a view explaining the first variation.

FIG. 9A is a view explaining the reference point setting method in afourth variation.

FIG. 9B is a view explaining the reference point setting method in afourth variation.

FIG. 10 is a flowchart showing details of processing in step S204.

DESCRIPTION OF EMBODIMENTS

Embodiments of the present invention will be described hereinafter indetail, with reference to the accompanying drawings. Note thatembodiments described below merely illustrate examples of specificallyimplementing the present invention, and are only specific embodiments ofa configuration defined in the scope of the claims.

First Embodiment

A medical image processing apparatus according to the present embodimentcalculates a “slippage” representing to what degree a region in amedical image slips with respect to a peripheral region, for eachposition-within-target-site (a position on a surface of a target site ora position in the target site) in a target site (organ). Theposition-within-target-site and the “slippage” calculated for theposition-within-target-site are then associated and displayed. Here, the“slippage” is a relative movement amount with respect to a targetperiphery. For example, due to respiratory movement of a lung, thesurface of the lung (also called visceral pleura) moves so as to slipwith respect to its periphery (also called parietal pleura). In such acase, the medical image processing apparatus according to the presentembodiment associates and display's a surface position of the lung and a“slippage” in the surface position. For such display, if there isadhesion between the surface of the lung and the periphery thereof (alsocalled pleural cavity), at a surface position for which adhesion ispresent, less “slippage” is displayed in comparison to the periphery.

Firstly, a block diagram of FIG. 1 is used to explain an exampleconfiguration of a medical image processing system that includes amedical image processing apparatus according to the present embodiment.Note that, as will be explained later, a configuration shown in FIG. 1is merely one example of a configuration of a medical image processingsystem to which the present embodiment is applicable, and anyconfiguration may be used if the configuration can realize processingexplained below.

As shown in FIG. 1, the medical image processing system according to thepresent embodiment has a medical image processing apparatus 10 and adatabase 22, and the medical image processing apparatus 10 and thedatabase 22 are connected to a LAN (Local Area Network) 21. Note thatwhile the medical image processing apparatus 10 and the database 22 maybe connected so that communication is possible therebetween; theconnection configuration between the medical image processing apparatus10 and the database 22 is not limited to the LAN 21.

Firstly explanation is given for the database 22. Stored in the database22 is medical image data for various sites of various patients, variouspieces of information corresponding to the medical image data (animaging target site, an image capturing condition, informationcorresponding to a patient, or the like), or the like. The medical imagedata includes a plurality of slice images (medical images) of a sitethat is an imaging target. By accessing the database 22 via the LAN 21,the medical image processing apparatus 10 can read the medical imagedata saved in the database 22 or various information corresponding tothe medical image data. Note that the database 22 may be a memoryapparatus in the medical image processing apparatus 10, without being anapparatus separate to the medical image processing apparatus 10.

Next, explanation is given for the medical image processing apparatus10.

A communication IF (Interface) 31 is realized by a LAN card or the like,and controls data communication between an external apparatus (forexample, the database 22) and the medical image processing apparatus 10via the LAN 21.

A ROM (Read Only Memory) 32 is realized by non-volatile memory or thelike, and, for example, stores setting data or a boot program for themedical image processing apparatus 10, or the like.

A RAM (Random Access Memory) 33 is realized by volatile memory or thelike, and, for example, has an area for storing a computer program ordata loaded from a memory unit 34, or data read from the database 22 viathe communication IF 31. Furthermore, a RAM 33 has a work area used whena control unit 37 executes processing. In this way the RAM 33 canappropriately provide various areas.

The memory unit 34 is a large capacity information storage devicerealized by an HDD (Hard Disk Drive) or the like. Saved in the memoryunit 34, for example, is an OS (operating system), computer programs forcausing the control unit 37 to execute or control various processingdescribed later as something the medical image processing apparatus 10performs, data, or the like. In addition, saved in the memory unit 34 isinformation handled as information known beforehand in the followingexplanation. The computer programs, data, or the like saved in thememory unit 34 are loaded into the RAM 33 as appropriate in accordancewith control by the control unit 37, and become a target of processingby the control unit 37.

An operation unit 35 is realized by a user interface such as a keyboardor a mouse, and by a user of the medical image processing apparatus 10operating the operation unit 35, various instructions can be input tothe control unit 37.

A display unit 36 is realized by a CRT, a liquid crystal screen, or thelike, and can display a result of processing by the control unit 37through images, text, or the like to thereby enable provision of variousinformation to a user (for example, a doctor).

The control unit 37 is realized by a CPU (Central Processing Unit) orthe like. By using a computer program, data or the like stored in theRAM 33 to execute processing, the control unit 37 performs operationcontrol of the medical image processing apparatus 10 on the whole, andalso executes or controls various later-described processing assomething that the medical image processing apparatus 10 performs.

The control unit 37 has, as a functional configuration thereof, a datareading unit 41, a target site extraction unit 42, a reference pointsetting unit 43, a registration unit 44, a movement informationcalculating unit 45, and a display processing unit 46. There are casesbelow in which explanation is given of a functional unit as a subject ofprocessing, but this means that a function of that functional unit iscaused to be realized by the control unit 37 executing a computerprogram corresponding to the functional unit out of computer programsstored in the RAM 33. However, one or more of these functional units maybe realized by using dedicated hardware, and software and/or hardwaremay used in any way to realize these functional units.

The data reading unit 41 accesses the database 22 via the communicationIF 31 or the LAN 21. The data reading unit 41 then reads from thedatabase 22 at least two pieces of medical image data (for example,X-ray CT image data captured at times different to each other (X-ray CTimage data for different time phases)), which become targets forregistration. The data reading unit 41 then sends the read medical imagedata to the target site extraction unit 42 and the registration unit 44.Note that below, medical image data that becomes a reference forregistration is referred to as a reference image, and medical image datafor which registration is performed with respect to this reference imageis referred to as a floating image.

The target site extraction unit 42 performs processing, which isdescribed later, with respect to at least one piece of the medical imagedata sent from the data reading unit 41 (for example, the referenceimage) to thereby acquire outline information, which is information fordefining an outline of the target site. The outline information may beany information if it is information that can define the outline of thetarget site on a respective s lice image included in the medical image,data, but hereinafter, the outline information is information thatdefines a pixel position (coordinates) for each pixel that configuresthe outline. However, the outline information may be any informationthat simply indicates the pixel position of each pixel that configuresthe outline, and, for example, may be an equation that represents theoutline. The target site extraction unit 42 then sends the acquiredoutline information to the reference point setting unit 43.

By using the outline information acquired by the target site extractionunit 42 to execute processing which is described later, the referencepoint setting unit 43 sets reference points for each of a target-siteside (an organ side) and a target site periphery side (a periphery sidethat faces the organ side) which are across from each other over theoutline of the target site. The reference point setting unit 43 thensends information indicating a position for each set reference point tothe movement information calculating unit 45.

By performing a known deformation registration of one piece of medicalimage data of the two pieces of medical image data sent from the datareading unit 41 with respect to the other piece of the medical imagedata, the registration unit 44 calculates pixel positions in the otherpiece of medical image data that correspond to respective pixels in theone piece of medical image data. The registration unit 44 then sendsinformation indicating the pixel positions in the other piece of medicalimage data that correspond to the respective pixels in the one piece ofmedical image data, i.e. information indicating a pixel positioncorrespondence relationship between the pieces of medical image data, ascorresponding pixel position information, to the movement informationcalculating unit 45. According to this embodiment, pixel positions(coordinates) for pixels in the floating image that correspond to pixelsthat comprise the reference image are corresponding pixel positioninformation.

The movement information calculating unit 45 uses “informationindicating position of each reference point” sent from the referencepoint setting unit 43 and the “corresponding pixel position information”sent from the registration unit 44 to execute later describedprocessing, and thereby calculates a “slippage” (a movement amountrelative to a periphery) for each pixel (an outline configuration point)that comprises the outline of the target site. The movement informationcalculating unit 45 then sends the slippage obtained for each outlineconfiguration point to the display processing unit 46.

The display processing unit 46 displays the “slippage” for each outlineconfiguration point calculated by the movement information calculatingunit 45 on the display unit 36. Various display forms can be consideredfor a display form of the “slippage” for each outline configurationpoint. For example, for one or more slice images included in medicalimage data, displaying is performed after luminance values of outlineconfiguration points in the slice images are converted to a grayscalevalue or a color scale value in accordance with the slippage obtainedfor the outline configuration points.

Note that, a portion of the above-described functional units explainedas a functional configuration of the control unit 37 may be assigned toan external apparatus (for example, a server apparatus via a network,such as a cloud server) separate to the medical image processingapparatus 10. In such a case, the medical image processing apparatus 10advances processing while performing data communication with theexternal apparatus.

Next, FIGS. 2 to 4A, 4B are used to give an explanation regardingoperation of the medical image processing apparatus 10. Hereinafter,explanation is given for a case in which the data reading unit 41 readsfrom the database 22 two pieces of medical image data acquired aftercapturing a chest region for a single patient at two points in time atwhich inhalation amounts differ by using an X-ray CT apparatus. Thetarget site extraction unit 42 then sets the target site (organ) forwhich to extract the outline as a lung, and calculates the “slippage”(slippage of pleura) in relation to the periphery (can also be calledparietal pleura) of positions on the surface of the lung (can also becalled visceral pleura). However, that each process described below isnot limited to these examples is clear from the following explanation,if one is skilled in the art.

<Step S201>

The data reading unit 1 accesses the database 22 via the communicationIF 31 and the LAN 21, and as described above, reads “two pieces ofmedical image data acquired after capturing a chest region for a singlepatient at two points in time at which inhalation amounts differ byusing an X-ray CT apparatus” from the database 22.

Note that the two pieces of medical image data acquired after capturingat two points in time at which inhalation amounts differ are, forexample, image data that is for two points in time that are temporallydifferent and is acquired by using a conventional X-ray 4D-CT apparatusto perform capturing without specifying a respiratory condition for apatient (without breath holding). The two pieces of medical image dataacquired by capturing at two points in time for at which inhalationamounts differ may be two pieces of CT image data, captured in a statein which the patient has fully exhaled a breath (exhalation state), anda state in which the breath is fully inhaled (inhalation state).

<Step S202>

In step S201, the target site extraction unit 42 extracts a region in alung field, by a method below, from one of the two pieces of medicalimage data read by the data reading unit 41 (a reference image), andthen acquires outline information of the extracted region (outlineinformation for the lung field).

The target site extraction unit 42 first uses a smoothing filter toperform noise reduction on the reference image (in other words, eachslice image included in the one piece of medical image data of the twopieces of medical image data read by the data reading unit 41 in stepS201). The target site extraction unit 42 then uses a predeterminedthreshold (for example, −200 HU) to perform binary conversion processingon the reference image on which noise reduction has been performed, tothereby separate regions in the reference image into an inside-bodyregion and an outside-body region. The target site extraction unit 42then uses a different threshold (for example, −500 HU) on theinside-body region in the reference image to separate the inside-bodyregion into a region in the lung field and another region, and to obtaina pixel position for each pixel that configures an outline (a boundaryof the region in the lung field and the other region) of the region inthe lung field According to this type of processing, it is possible toobtain the pixel position for each pixel that configures the outline ofthe target site in the reference image, i.e. the outline information.

Note that in the target site extraction processing, it is sufficientthat a region determined from the reference image can be extracted, andlimitation is not made to the present approach. For example,conventional segmentation processing, such as graph cut processing, maybe used to extract the target site. Alternatively, not shown diagramdrawing software may be used to render the outline for the target sitemanually by a user, and extract the outline information from therendered outline. Alternatively, after the target site is automaticallyextracted by a conventional approach (the above-described binaryconversion processing, segmentation processing, or the like), theoutline information may be extracted after an automatically extractedoutline is corrected manually by a user.

<Step S203>

The reference point setting unit 43 uses the outline informationacquired by the target site extraction unit 42 to execute the processingexplained below and thereby set reference points for each of atarget-site side and a target site periphery side which are across fromeach other over the outline of the target site in the reference image.In other words, the reference point setting unit 43 sets a firstreference point for the target-site side, sets a second reference pointfor the periphery side that opposes target-site side from across theoutline, and furthermore sets a plurality of first reference point andsecond reference point pairs. In the following processing, movementinformation for the second reference points is calculated with respectto the first reference points. FIGS. 3A to 3C are used to give anexplanation regarding the reference point setting method by thereference point setting unit 43. Note that in FIGS. 3A to 3C in order tosimplify the explanation only a partial region in the reference image isshown, and below such FIGS. 3A to 3C are used to explain a method ofsetting reference points in the partial region. However, actuallysimilar processing is performed with regards to all regions of thereference image.

In FIG. 3A, the reference number 301 is an axial plane chest CT image ina specific slice position (Z=1), and the reference number 302 denotesoutlines of regions in a lung field acquired from a chest CT image 301in step S202. The reference number 304 denotes a pixel group in a region303 shown by broken lines in the chest CT image 301. Boxes filled inblack in the pixel group 304 represent pixels that configure the outline302 in the region 303 (outline configuration points), and boxes filledin white represent pixels that configure a region other than the outline302 in the region 303.

Here, setting a position of an upper left corner of the pixel group 304as an origin, if the rightward direction is taken as the X axis and thedownward direction is taken as the Y axis, it is possible to express apixel position for each pixel that comprises the pixel group 304 in anXYZ coordinate system. In other words, the pixel positions (coordinates)for the pixels that comprise the outline 302 become (1,1,1), (2,2,1),(3,2,1), (4,3,1), (5,4,1), (6,5,1), (6,6,1), (7,7,1), (8,8,1), (9,9,1),(9,10,1).

Here reference points are set in pairs of the target-site side (in thelung field) and the periphery side (outside the lung field) for all theoutline configuration points. For example, reference pointscorresponding to an outline configuration point are set at positionsseparated by a fixed distance along a normal direction towards each ofthe target-site side and the periphery side from the center of a linesegment connecting two outline configuration points that are adjacent tothe outline configuration point (that sandwich the outline configurationpoint). In the case of FIGS. 3A to 3C, when setting reference pointscorresponding to the outline configuration point at coordinates (4,3,1),firstly a line segment (reference numeral 305 of FIG. 3B) that connectsthe coordinates (3,2,1) and coordinates (5,4,1), the two outlineconfiguration points that are adjacent to the outline configurationpoint, is set. Then a reference point is set at each of a positionseparated a fixed distance along the normal direction from the center ofthe line segment 305 to the target-site side, and a position separated afixed distance along the normal direction from the center of the linesegment 305 to the periphery side. In the present example, the “fixeddistance” is “two pixels”. In FIG. 3B, a pixel 306 and a pixel 307 (inother words a pixel at coordinates (2,5,1) and a pixel at coordinates(6,1,1)) shown with diagonal lines are set as reference points. Thepixel 306 is a reference point for the target-site side, and the pixel307 is a reference point for the periphery side. FIG. 3C shows areference point group (the group of boxes shown with diagonal lines) setfor all the outline configuration points in the pixel group 304. Notethat FIG. 3C shows an example in which reference points corresponding toeach outline configuration point included in the pixel group 304 areincluded in the pixel group 304, but in accordance with the value of theabove described “fixed distance” or a distribution of the outlineconfiguration points, there are cases in which a reference point is setoutside of the pixel group 304.

Note that if the reference points are set as a pair for the target-siteside and the periphery side, for each of the outline configurationpoints, the reference points may be set at any position. For example,they may be set on straight lines extended along the normal directionsof the line segment that connects the two outline configuration pointsadjacent to the focus outline configuration point so as to pass throughthe focus outline configuration point at positions that are a fixeddistance from the focus outline configuration point. Also, in accordancewith an orientation of the line segment connecting two outlineconfiguration points that are adjacent to an outline configurationpoint, the distance by which they are separated from the line segmentmay be changed.

Also, reference points may be set both on the outline of the targetsite, and on either the target-site side or the periphery side of thetarget site with reference to the outline. In other words, a referencepoint of either the target-site side or the periphery side may be thecorresponding outline configuration point itself. In other words,reference points may be set on the outline and on the target-site side(or on the periphery side of the target site).

Specifically, the reference point setting unit 43 uses the outlineinformation acquired by the target site extraction unit 42 to set areference point on each of on the outline of the target site, and eitherthe target-site side and the periphery side of the target site, based onthe outline. The reference point setting unit 43 then sends informationindicating a position for each set reference point to the movementinformation calculating unit 45.

The movement information calculating unit 45 uses the “informationindicating the position of each reference point” sent from the referencepoint setting unit 43 and the “corresponding pixel position information”sent from the registration unit 44 to calculate the movement informationfor the reference points of the outline and the reference points set inthe target-site side (or in the periphery side of the target site otherwords, the “slippage” (a movement amount relative to the periphery) ineach pixel (outline configuration point) that configures the outline ofthe target site organ is calculated. Thereby, it is possible tocalculate the slippage for the target site with regard to the peripheryof the target site, based on the movement information for the referencepoints. Setting of the reference points, as shown in FIGS. 3A to 3C, maybe implemented in each slice for the reference image after settingtwo-dimensional coordinates therein, or three-dimensional coordinatesmay be set for three-dimensional volume data. Furthermore, the referencepoints may be set for all outline configuration points that configurethe outline acquired in step S202 as in the present embodiment, or maybe set only for outline configuration points at fixed intervals. Inaddition, setting may be performed with respect to only positions on theoutline that a user designates.

<Step S204>

Towards one (the reference image) of the two pieces of medical imagedata that the data reading unit 41 read in step S201, the registrationunit 44 performs deformation registration of the other piece (thefloating image). For the deformation registration, conventionaldeformation registration processing, such as an FFD (Free-FormDeformation) method or an LDDMM (Large Deformation Diffeomorphic MetricMapping) method, is applicable. Any of such deformation registrationmaintains a normal structure of the target site in the medical imagedata.

By such processing, it is possible to calculate (acquire correspondingpixel position information) the pixel positions on the floating imagethat correspond to each pixel in the reference image. Here, if adifference in inhalation amount for each of the reference image and thefloating image is small, non-linear deformation registration processingas initially exemplified above may be performed, but if the differencein inhalation amount is large, deformation registration processing mayfail. In such a case, non-linear deformation registration processing maybe performed after performing known linear deformation registrationprocessing, such as an affine transformation, before performingnon-linear deformation registration processing.

Here, the processing of step S204 may be performed at any time if it isperformed after step S201 and before step S205. For example, theprocessing of step S204 may he performed before step S202, and may beperformed between step S202 and step S203. Furthermore, the processingof step S204 may be performed in parallel with step S202 and step S203.

<Step S205>

When performing registration between medical images (between pieces ofmedical image data) for different time phases, the movement informationcalculating unit 45 calculates movement information for the referencepoints set on the periphery side with respect to the reference pointsset on the target-site side, between the medical image for which thereference points are set and the medical image that is registered withrespect to the medical image for which the reference points are set. Inother words, the reference points set in step S203 and the correspondingpixel position information acquired in step S204 are used to calculatethe “slippage” in each outline configuration point. The “slippage” is anamount that the outline configuration point has moved with respect tothe periphery. FIGS. 4A and 4B are used to specifically explainprocessing in step S205.

FIG. 4A shows a pixel group in a partial region of the reference image,in which boxes filled in black, including boxes a-f, indicate outlineconfiguration points (pixels), and boxes filled in white indicatenon-outline configuration points (pixels). In addition, the pixelposition for each of the outline configuration points and thenon-outline configuration points is shown in an XYZ coordinate system.In addition, a_(i)-f_(i) each indicate a target-site side referencepoint corresponding to the outline configuration points a-f, anda_(o)-f_(o) each indicate a periphery side reference point correspondingto the outline configuration points a-f.

FIG. 4B shows a pixel group in a partial region in the floating image,and the pixel position for each pixel in the pixel group is shown in anX′Y′Z′ coordinate system. A_(i)-F_(i) respectively indicate pixelsdefined as pixels that correspond to a_(i)-f_(i) by the correspondingpixel position information, and A_(o)-F_(o) respectively indicate pixelsdefined as pixels that correspond to a_(o)-f_(o) by the correspondingpixel position information.

Here, coordinates for a target-site side reference point in thereference image at an outline configuration point P are set as (x_(i),y_(i), z_(i)), and coordinates for a pixel on the floating imagecorresponding to the reference point are set as (x_(i)′, y_(i)′,z_(i)′). Here, coordinates for a periphery side reference point in thereference image at an outline configuration point P are set as (x₀,y_(o), z_(o)), and coordinates for a pixel on the floating imagecorresponding to the reference point are set as (x_(o)′, y_(o)′,z_(o)′). At this point, a “slippage” S (movement information) at theoutline configuration point P can be calculated through the followingequation.

S=√(((x _(i) −x _(i)′)−(x _(o) −x _(o)′))²+((y _(i) −y _(i)′)−(y _(o) −y_(o)′))²+((z _(i) −z _(i)′)−(z _(o) −z _(o)′))²)

For example, if coordinates for a_(i) (2,5,1), coordinates for A_(i)(1,7,1), coordinates for a_(o) (6,1,1) and coordinates for A_(o) (5,2,1)are used to calculate the above-described equation, the “slippage” S is√(((2−1)−(6−5))²+((5−7)−(1−2))²+((1−1)−(1−1))²), which when calculatedgives S=1. As another example, if coordinates for c_(i) (4,7,1),coordinates for c_(i) (4,7,1), coordinates for c_(o) (8,3,1) andcoordinates for c_(o) (8,3,1) are used to calculate the above-describedformula, the “slippage” S is 0.

In this way, for each outline configuration point on the outline, the“slippage” is calculated based on the difference between the pixelpositions of the reference points set for the outline configurationpoints, and the pixel positions of the points defined by thecorresponding pixel position information as points on the floating imagethat correspond to the reference points. Note that if in step S203reference points are only set for a portion of outline configurationpoints from outline configuration point group, the “slippage” is onlycalculated for the outline configuration points for which referencepoints are set.

<Step S206>

The display processing unit 46 visualizes and displays on the displayunit 36 the slippage. In other words, as described above, the displayprocessing unit 46 displays the “slippage” for each outlineconfiguration point calculated by the movement information calculatingunit 45 on the display unit 36. Here, in a case where luminance foroutline configuration points in the medical image data is converted to agray scale value or a color scale value in accordance with the slippageobtained for the outline configuration points, the color scale orgrayscale may be predetermined, or may be changed dynamically. Forexample, the width of the grayscale and the median value thereof may bedetermined from a minimum value and a maximum value from the respectiveslippages calculated in step S205. Note that the visualization methodfor the “slippage”s described here is merely an example, and thevisualization method is not limited to this if aposition-within-target-site of the target site and the “slippage” at itsposition can be displayed in association. In addition, the luminances ofthe outline configuration points in a portion of the slice images,rather than all the slice images included in the medical image data, maybe converted to grayscale values or color scale values in accordancewith the slippages obtained for those outline configuration points, andthese may be displayed. This “a portion of the slice images” may beslice images selected by a user operating the operation unit 35, or maybe slice images selected by the control unit 37 on the basis of somecriteria.

Next, a test result performed by using the approach in the presentembodiment is discussed below. FIG. 5 is a view in which, for a patienthaving adhesion in a pleura, a mark is entered at a position at which arespiratory surgery department doctor could visually observe theadhesion when an open-chest operation is actually performed. Accordingto FIG. 5, it is seen that the adhesion for this patient is in a widerange from the right side between the third-fifth ribs slightly towardsa rearward direction. FIGS. 6A and 6B are views that visualize“slippage” using the approach in the present embodiment with respect toan X-ray 4D-CT image for the same patient as FIG. 5 before theoperation. FIG. 6A is a view of a 3D image that visualizes the“slippage” in the present embodiment from the perspective of the rightlateral side of the patient, and FIG. 6B is a view from the perspectiveof a left lateral side. In FIGS. 6A and 6B, the “slippage” is shown in agrayscale, and closer to white indicates a region for which the“slippage” is higher (more slippage), and closer to black indicates aregion for which the “slippage” is lower (does not slip as much). Here,focusing on a region 601 of FIG. 6A, it is rendered as relatively blackin comparison to the periphery thereof. This is more noticeable whencompared to the same position of FIG. 69, on the opposite side.Positions rendered as relatively black in the region 601 issubstantially the same as the adhesion positions of the pleura shown inFIG. 5. Furthermore, when a respiratory surgery department doctor and aradiation department doctor who are medical specialists ininterpretation confirm the images of FIGS. 6A and 6B, a conclusion thatit is possible to visualize approximately the same region from ananatomical structure of the periphery was reached. From these results,it can be said that it is actually possible to visualize the adhesionposition of the pleura in the approach in the present embodiment.Accordingly, because the position of adhesion is known from the imagedmedical image data before the operation, there is the effect that it ispossible to avoid unnecessary risk when performing an operation.

In this way, according to the present embodiment, because it is possibleto visualize differences in “slippage” in differences in aposition-within-target-site in the target site, a user can recognize theposition-within-target-site that has “slippage” that is different to theperiphery, and can recognize the existence/absence of an abnormality ofa target site, a position of an abnormality, or the like.

(First Variation)

In step S201 of the first embodiment, two pieces of medical image dataacquired after capturing at two point in times at which the inhalationamount is different are read. However, the number of pieces of themedical image data read in step S201 may be three or more. For example,configuration may be performed to use the X-ray 4D-CT apparatus in astate in which the patient does not stop respiration to read from thedatabase 22 medical image data that is for many points in time and iscaptured at a specific interval. FIGS. 7A-7D, 8 are used to explain themedical image data for many points in time.

FIGS. 7A, 7B, 7C, 7D show slice images (medical images) (portion) inmedical image data captured at points in time T1, T2, T3, and Tn (n isan integer greater than or equal to 4), respectively, and pixelpositions in the medical image data are expressed by an XYZ coordinatesystem. In the present variation, as an example, T1 is the considered asa reference. In this case, extraction of the outline of the target sitein step S202 or setting of the reference points in step S203 isperformed with respect to the medical image data captured at the pointin time T1. However, a point in time other than may be the reference.

In FIG. 7A T1 i is a reference point (the coordinates thereof are(2,5,1)) of the target-site side corresponding to an outlineconfiguration point (an outline configuration point Q), and T1 o is areference point (the coordinates thereof are (3,2,1)) of the peripheryside corresponding to the outline configuration point Q. In FIG. 7B T2 iand T2 o are corresponding points defined as points that correspond toT1 i and T1 o, respectively, by corresponding pixel position informationacquired by performing the above-described deformation registration onmedical image data that includes the slice image of FIG. 7A as thereference image and medical image data that includes the slice image ofFIG. 7B as the floating image. Coordinates of point T2 i are (4,5,1),and coordinates of point T2 o are (4,1,1). The slippage S of the outlineconfiguration point Q, acquired by substituting coordinates of thereference points T1 i and T1 o and coordinates of T2 i and T2 o into theabove-described equation, is “2”.

In FIG. 7C, T3 i and T3 o are corresponding points defined as pointsthat correspond to T1 i and T1 o, respectively, by corresponding pixelposition information acquired by performing the above-describeddeformation registration on medical image data that includes the sliceimage of FIG. 7A as the reference image and medical image data thatincludes the slice image of FIG. 7C as the floating image. Coordinatesof point T3 i are (5,5,1), and coordinates of point T3 o are (4,1,1).Here, the slippage S of the outline configuration point Q, acquired bysubstituting coordinates of the reference points T1 i and T1 o andcoordinates of T3 i and T3 o into the above-described equation, is “5”.

In FIG. 7D Tni and Tno are corresponding points defined as points thatcorrespond to T1 i and T1 o, respectively, by corresponding pixelposition information acquired by performing the above-describeddeformation registration on medical image data that includes the sliceimage of FIG. 7A as the reference image and medical image data thatincludes the slice image of FIG. 7D as the floating image. Coordinatesof point Tni are (2,5,1), and coordinates of point Tno are (2,1,1).Here, the slippage S of the outline configuration point Q, acquired bysubstituting coordinates of the reference points T1 i and T1 o andcoordinates of Tni and Tno into the above-described, equation, is “2”.

In this way, it is possible to calculate the “slippage” that uses T1 asa reference, based on the medical image data of each point in time. Inthe present variation, in step S205, for each outline configurationpoint, a portion or all of the “slippage” at each point in time obtainedfor the outline configuration point is used to calculate a “secondslippage” for the outline configuration point. For example, an averagevalue across all points in time of the “slippage”s of the respectivepoint in time may be set as the “second slippage”, or a maximum value ofthe “slippage” across all points in time may be set as the “secondslippage”. Here, because respiration is a periodic motion, the“slippage” for a reference point in time (T1 in the present example) inthe respective points in time also changes periodically as in FIG. 8. Inother words, if the number of pieces of data read is greater than orequal to a constant, it is possible to obtain a periodic function forthe “slippage” with respect to the reference point in time, as in FIG.8. In this case, the amplitude or period of the periodic function isused to calculate the “second slippage”.

Then in step S206 of the present variation, the display processing unit46 performs processing similar to that of the first embodiment so as tovisualize the “second slippage”. In other words, luminances of outlineconfiguration points in the medical image data are converted tograyscale values or color scale values in accordance with the “secondslippage” obtained for the outline configuration points, and thepost-conversion medical image data is displayed.

Note that the method of calculating the “second slippage” explained hereis one example, and the method of calculating the “second slippage” isnot limited to this if it can use the “slippage”s of a plurality ofpoints of time to represent a relative movement amount with respect tothe periphery of each position-within-target-site in the target site.

Note that, in addition to the present variation, variations andembodiments explained below are predominantly explained as bydifferences with the first embodiment, and unless particularly touchedupon are similar to the first embodiment.

(Second Variation)

For the first embodiment, in step S204 two differing pieces of medicalimage data are used to perform deformation registration. However,medical image data for a plurality of points in time may he used togradually perform registration of the reference image and the floatingimage, and to calculate the “slippage”. FIGS. 7A-7D are used to explainthe present variation.

Here the medical image data that includes the slice image shown in FIG.7A is set as the reference image, and the medical image data thatincludes the slice image shown in FIG. 7D is set as the floating image.The medical image data that includes the slice image of FIG. 7A, themedical image data that includes the slice image of FIG. 7B, the medicalimage data that includes the slice image of FIG. 7C, and the medicalimage data that includes the slice image of FIG. 7D are captured in atemporal sequence in this order (in other words T1<T2<T3<Tn).

Firstly, the reference image and the medical image data of point in timeT2 adjacent thereto (the medical image data that includes the sliceimage of FIG. 7B) are used to perform deformation registration (calleddeformation processing 1), and to calculate the points T2 i and T2 o, onthe medical image data that includes the slice image of FIG. 7B,corresponding to each of the reference points T1 i and T1 o.

Next, the medical image data that includes the slice image of FIG. 7B,and the medical image data (the medical image data that includes theslice image of FIG. 7C) of a point in time that is a point in timeadjacent thereto and that is a point in time (T3 in the case of FIGS.7A-7D) closer to the point in time Tn are used to perform deformationregistration. According to this deformation registration, points T3 iand T3 o, on the medical image data of FIG. 7C, corresponding to each ofthe reference points T2 i and T2 o are calculated.

In this way similar processing is repeated, and medical image data of apoint in time T(n−1), and medical image data of a point in time that isadjacent thereto and that is a point in time closer to the point in timeTn (in other words Tn) are used to perform deformation registration.According to this deformation registration, points Tni and Tno, on themedical image data of point in time Tn, corresponding to the referencepoints T(n−1)i and T(n−1)o, respectively, are calculated.

In this way, in a case where medical image data of a plurality of pointsin time is used to gradually perform deformation registration, the“slippage” is calculated by using a reference image which is the medicalimage data of the point in time T1, and the floating image which is themedical image data of the point in time Tn. If the above-describedequation is calculated by using the coordinates of T1 i (2,5,1) and thecoordinates of Tni (2,5,1) as well as the coordinates of T1 o (3,2,1)and the coordinates of Tno (2,1,1), 2 is calculated as the “slippage”.

If a difference between medical image data of two points in time islarge, deformation registration processing may fail. However, accordingto the present variation, even if a difference between the referenceimage and the floating image is large, the positions thereof areregistered gradually, so there is the effect that it is possible tocorrectly perform registration.

(Third Variation)

In the first embodiment, in step S204 and step S205, the correspondingpixel position information is acquired from a result of deformationregistration processing with respect to the reference image and thefloating image, which have the same image condition. However, thedeformation registration processing may be performed to acquire thecorresponding pixel position information after changing the imagecondition of the reference image and the floating image in accordancewith the position of a reference point. In other words, registration maybe performed between medical images (medical image data) that are atarget of registration, after correcting the medical images that are thetarget of registration in accordance with an image conditioncorresponding to a position at which a reference point is set. Thisimage condition differs for a position of a reference point of thetarget-site side, and a position of a reference point of the peripheryside of the target site. Below, as an example, explanation is given fora case in which the target site is a lung. In step S204, for a positionof a point on the floating image corresponding to a reference point ofthe target-site side, density values of the reference image and thefloating image are set to conditions suitable to observation of a lungfield (for example, WL at −600, WW at 1500), deformation registrationprocessing is performed, and acquisition is performed using the resultthereof. In step S204, for a position of a point on the floating imagecorresponding to the reference point of the periphery side, densityvalues of the reference image and the floating image are set toconditions suitable to observation of a mediastinum (for example, WL at60, WW at 400), deformation registration processing is then performed,and acquisition is performed using the result thereof. Then in stepS205, for each reference point, the corresponding pixel positioninformation acquired under the suitable image condition is used tocalculate the “slippage”.

For regions in which anatomical characteristics of the target site aredifferent as in the inside and outside of a lung, image characteristicsof the medical image data also differs. If deformation registrationprocessing is performed collectively for such regions having differingmedical image data image characteristics, there may be a failure.According to the present variation, suitable image conditions are usedfor each of regions in which characteristics of the medical image datadiffer to perform the deformation registration processing. Thereby, itis possible to perform correct deformation registration processing withrespect to each region. Accordingly, there is the effect that even ifreference points are set with respect to regions for whichcharacteristics of the medical image data differs, it is possible tocalculate the corresponding pixel position information correctly withrespect to each reference point.

(Fourth Variation)

In the first embodiment, in step S203, reference points for an outlineconfiguration point are set at positions separated by a fixed distancealong normal directions from the center of a line segment connecting twooutline configuration points adjacent to the outline configurationpoint. However, the setting method of the reference points is notlimited to this. For example, an anatomical structure in the medicalimage data may be used to intentionally set a region (hereinafterreferred to as an exclusion region) in which reference points are notset. For example, a bone region, a blood vessel region, or the like maybe set as an exclusion region. Hereinafter, the exclusion region, whichis a region in which reference points are not set, is acquired from themedical image (medical image data), and the reference points are setoutside the exclusion region in the medical image. Here, a case in whicha bone region is acquired as the exclusion region and the referencepoints are set outside the exclusion region is explained as an example.

Firstly, a known segmentation method, such as graph cut processing, isused to extract the bone region in the body from the medical image data.Of course, an approach for extracting the bone region is not limited tothis, and configuration may be taken so that: the medical image data isdisplayed on the display unit 36: a user operates the operation unit 35,while watching the medical image data that is displayed, to manuallyselect the bone region; and the selected bone region is therebyextracted.

Next, if a position (for example, a position separated by a fixeddistance along a normal direction) of a reference point set inaccordance with step S203 for each outline configuration point overlapswith the bone region, the reference point is set to a position furtherseparated along the normal direction, so as to not overlap with the boneregion. FIGS. 9A and 9B are used to explain details for this referencepoint setting method.

FIG. 9A shows a state in which a bone region 902 is included in thepixel group 304. The pixel positions of each pixel that configures thebone region 902 are (7,2,1), (8,2,1), (9,2,1), (7,3,1), (8,3,1),(9,3,1), (7,4,1), (8,4,1), (9,4,1). Explanation is given for a case inwhich in such a state, as the method of setting the reference points ofthe outline configuration points, a method of setting at positions forwhich a distance separated from the center of a line segment connectingtwo outline configuration points adjacent to the outline configurationpoint and along a normal direction is just two pixels is employed.

If such a reference point setting method is followed with, in step S203the coordinates of a target-site side reference point become (2,5,1),and coordinates of a periphery side reference point become (6,1,1) forthe position of a point a in FIGS. 9A and 9B. Next reference points forthe position of a point b is considered. According to theabove-described reference point setting method, the coordinate of thetarget-site side reference point become (3,6,1), and coordinates of theperiphery side reference point become (7,2,1) for the position of apoint b, but coordinates (7,2,1) are coordinates that are inside thebone region. In such a case, a position further separated by just onepixel along the normal direction is re-set as the position of thereference point. In other words, the periphery side reference point forthe position of the point b is set at the coordinates (8,1,1). Here, ifthe position separated by just one pixel is once again in the exclusionregion, setting is performed to a position further separated by onepixel. In this way, until the reference point is set at a positionoutside the exclusion region, the position set for the reference pointis changed to a position separated along a normal direction. FIG. 9Bshows target-site side reference points ai-fi and periphery sidereference points ao-fo for positions of points a-f in FIGS. 9A and 9B.

According to processing of the present variation, if a reference pointfor an outline configuration point is set at a position separated by afixed distance or more (for example, 50 pixels or more), it may not bepossible to calculate a “slippage” that meets the intention of a user.Accordingly, if a reference point is set to a position that is separatedby a predetermined fixed distance or more, configuration may be taken tonot calculate a “slippage” for the outline configuration pointcorresponding to that reference point.

According to the present variation, because it is possible to avoidsetting a reference point in a region of the target site in the medicalimage data in which anatomical characteristics are different, it ispossible to obtain the movement amount in a state where conditions matchbetter, for each outline configuration point.

(Fifth Variation)

For the first embodiment, in step S205 the reference points set in stepS203 and the corresponding pixel position information acquired in stepS204 are used to calculate the “slippage” for each the outlineconfiguration point. However, for calculation of the “slippage”, otherinformation may be used. For example, in a normal state for the lungs,the caudal side thereof (close to the diaphragm) has a large movementamount in comparison to the cranial side thereof (close to the apexpulmonis), and in other words has a large “slippage”. Accordingly, ifthe magnitude of the “slippage” is simply visualized, there is thepossibility that recognition of a region having an abnormal “slippage”will become difficult. Accordingly, from temporal medical image data ofmany normal lungs, a model reflecting movement of a normal lung isgenerated, and the model may be used to obtain a correction coefficientfor “slippage” of the caudal side region and of the cranial side region,and applied to the “slippage” of each outline configuration point. Inother words, the slippage obtained for each position on the surface ofthe target site or for each position in the target site may be correctedby using a correction coefficient set for each position on the surfaceof the target site or of for each position in the target site. Forexample, for a region in which the “slippage” is large in a normal state(for example, the caudal side region), a correction coefficient thatreduces the “slippage” is calculated, and for a region in which the“slippage” is small in a normal state (for example, the cranial sideregion), a correction coefficient that enlarges the “slippage” iscalculated. Then the movement information calculating unit 45 uses thecalculated correction coefficients to normalize (correct) the “slippage”for each outline configuration point (for example, the “slippage” ismultiplied by the correction coefficient). Thereby, it is possible tocalculate “slippage” that better matches the intention of a user. Notethat in the present variation, the method of normalizing the “slippage”for each outline configuration point based on normal movement of thetarget site is just one example, and other methods may be used toachieve a similar objective. For example, normalizing may be performedby using medical image data temporally captured in the past for the samepatient. At that time, it is possible to visualize a region in which adifference in “slippage” is large with respect to the past. Also, if atarget site exists for which the left and the right thereof aresymmetrical, such as with the lungs, the “slippage” of the symmetricaltarget site of the target site may be used to perform normalizing.

(Sixth Variation)

In the first embodiment, explanation was given for an example applied tomedical image data captured by an X-ray CT apparatus, such as an X-ray4D-CT image. However, modality is not limited to an X-ray CT apparatus,if it is possible to obtain medical image data that differs temporally(for a lung field, medical image data for which an inhalation amountdiffers).

For example, in the case of a simple X-ray photograph, medical imagedata for a state in which a breath is fully inhaled (inhalation imagedata), and medical image data for a state in which a breath is fullyexhaled (exhalation image data) is captured under the same imagecapturing conditions (tube current, tube voltage, irradiation period,irradiation distance). Similar to a CT image, processing of stepS202-step S206 may be performed with respect to these two pieces ofmedical image data. Note that in a case of the simple X-ray photograph,because it is a 2D image, it is predicted that a rib region is animpediment when a lung field region is extracted. In such a case, aconventional rib extraction method may be used to remove the rib regionfrom the medical image data, and thereafter conventional segmentationprocessing may be used to extract the lung field.

In addition, even for medical image data captured by using an MRIapparatus, an ultrasonic apparatus or the like, it is possible to obtainmedical image data for at least two temporally different points in time,and if the region of the target site can be extracted, it is possible toapply similar processing.

Second Embodiment

In the first embodiment, reference points are set on the target-siteside and the periphery side across from each other over an outline foreach outline configuration point of the target site, and the “slippage”is calculated based on corresponding pixel position information for eachreference point. In the second embodiment, the outside (the peripheryside) of the outline of the target site is fixed, and the “slippage” iscalculated from the corresponding pixel position information of eachreference point in the inside (the target-site side).

Although a configuration of the medical image processing apparatus 10and a configuration of the medical image processing system according tothe present embodiment are similar to that of the first embodiment,processing performed by the medical image processing apparatus 10 ischanged from the processing in accordance with the flowchart of FIG. 2as follows. Note that below, explanation is given with the target siteas a lung, similarly to the first embodiment. The action of stepS201-step S203 is similar to the processing in the first embodiment. Instep S204, processing in accordance with the flowchart of FIG. 10 isperformed.

<Step S1001>

The registration unit 44 performs the deformation registrationprocessing after setting the density value for each of the referenceimage and the floating image to conditions (for example, WL as 60 and WWas 400) suitable to the display of the periphery side (a soft partregion, such as muscle or the like). Here, an image generated byperforming the deformation registration processing on the referenceimage with respect to the floating image under conditions suitable todisplay of the periphery side is referred to as a provisional image.

<Step S1002>

The registration unit 44 performs the deformation registrationprocessing after setting the density value for each of the referenceimage and the provisional image to conditions (for example, WL as −600and WW as 150) suitable to the display of the target site (organ side:the lung field region). Then the registration unit 44 calculates thepixel positions on the provisional image corresponding to respectivepixels on the reference image (acquires the corresponding pixel positioninformation). Here, the positions of periphery side reference points onthe reference image and positions of corresponding points on theprovisional image, which correspond to the reference points, shouldsubstantially match by the processing of step S1001. In other words, ina state in which the periphery side reference points for each outlineconfiguration point are fixed, it is possible to acquire thecorresponding pixel position information for the target-site sidereference points through processing of step S1002. Here, it can heconsidered that the target-site side reference points for respectiveoutline configuration points corresponding to position having adhesionalso substantially match by the processing of step S1001, similar to theperiphery side reference points. This is because even in the target-siteside region, it can be considered that a region that is firmly joined,such as by adhesion, to the periphery side will track movement of theperiphery side. Accordingly, the “slippage” of the target-site sidereference points for respective outline configuration pointscorresponding to positions at which there is adhesion becomes smaller incomparison to a position at which there is no adhesion.

In step S205, the movement information calculating unit 45 uses thetarget-site side reference points from the reference points set in stepS203, and the corresponding pixel position information for thetarget-site side reference points, from the corresponding pixel positioninformation acquired in step S204, to calculate the “slippage” for eachoutline configuration point. In other words, the corresponding pixelposition information for the periphery side reference points is notused. More specifically, coordinates for a target-site side referencepoint in the reference image at an outline configuration point P are setas (x_(i), y_(i), z_(i)), and coordinates for a pixel on the provisionalimage corresponding to the reference point are set as (x_(i)′, y_(i)′,z_(i)′). At this time, the “slippage” S2 of that outline configurationpoint can be obtained by calculating the following equation.

S2=√((x _(i) −x _(i)′)²+(y _(i) −y _(i)′)²+(z _(i) −z _(i)′)²)

The processing in step S206 is similar to that of the first embodiment.In this way, according to the present embodiment, it is possible tovisualize differences in “slippage” for surface positions of the targetsite. Accordingly, a user can recognize a region having “slippage” thatis different to the periphery of the target site, and can recognize thepresence/absence of an abnormality of the target site, the position ofan abnormal location, or the like. Note that the above-explainedembodiments and variations may be implemented by appropriately combiningall or parts thereof.

In this way, each of the first and second embodiments and thefirst-sixth variations is merely an example of a medical imageprocessing apparatus comprising: an acquisition unit that acquiresmedical image data for of differing time phases, an extraction unit thatextracts a target site with respect to at least one piece of the medicalimage data acquired in accordance with the acquisition unit, a settingunit for respectively setting a reference point on an outline of thetarget site extracted by the extraction unit, and setting a referencepoint on either a target-site side or a periphery side of the targetsite, making the outline a reference, and a movement informationcalculating unit that calculates movement information for the referencepoint set by the setting unit, and further variations can be consideredif they have a configuration that resolves to a similar configuration.

Other Embodiments

Embodiment(s) of the present invention can also be realized by acomputer of a system or apparatus that reads out and executes computerexecutable instructions (e.g., one or more programs) recorded on astorage medium (which may also be referred to more fully as a‘non-transitory computer-readable storage medium’) to perform thefunctions of one or more of the above-described embodiment(s) and/orthat includes one or more circuits (e.g., application specificintegrated circuit (ASIC)) for performing the functions of one or moreof the above-described embodiment(s), and by a method performed by thecomputer of the system or apparatus by, for example, reading out andexecuting the computer executable instructions from the storage mediumto perform the functions of one or more of the above-describedembodiment(s) and/or controlling the one or more circuits to perform thefunctions of one or more of the above-described embodiment(s). Thecomputer may comprise one or more processors (e.g., central processingunit (CPU), micro processing unit (MPU)) and may include a network ofseparate computers or separate processors to read out and execute thecomputer executable instructions. The computer executable instructionsmay be provided to the computer, for example, from a network or thestorage medium. The storage medium may include, for example, one or moreof a hard disk, a random-access memory (RAM), a read only memory (ROM),a storage of distributed computing systems, an optical disk (such as acompact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™)a flash memory device, a memory card, and the like.

While the present invention has been described with reference toexemplary embodiments, it is to be understood that the invention is notlimited to the disclosed exemplary embodiments. The scope of thefollowing claims is to be accorded the broadest interpretation so as toencompass all such modifications and equivalent structures andfunctions.

This application claims the benefit of Japanese Patent Application No.2014-203344, filed Oct. 1, 2104, which is hereby incorporated byreference herein in its entirety.

1. A medical image processing apparatus comprising: an acquisition unitconfigured to acquire a plurality of medical images in time phases; anextraction unit configured to extract a target site from at least onemedical image from the plurality of medical images; a setting unitconfigured to set a reference point on each of a target-site side, and aperiphery side of the target site based on an outline of the target siteextracted by the extraction unit; and a calculation unit configured tocalculate movement information for the reference points set by thesetting unit, wherein the setting unit is configured to set a pluralityof pairs of a first reference point on the target-site side and a secondreference point on the periphery side, and wherein the calculation unitis configured to calculate the movement information of the secondreference point with respect to the first reference point.
 2. Themedical image processing apparatus according to claim 1, wherein thesetting unit is configured to set the first reference point on thetarget-site side, and set the second reference point on the peripheryside, which opposes the target-site side across the outline. 3.-4.(canceled)
 5. The medical image processing apparatus according to claim1, wherein the calculation unit is configured to calculate a slippage ofthe target site with respect to the periphery of the target site, basedon the movement information for the reference point.
 6. The medicalimage processing apparatus according to claim 5, further comprising adisplay unit configured to visualize and display the slippage.
 7. Themedical image processing apparatus according to claim 1, furthercomprising a registration unit configured to perform registrationbetween medical images of different time phases, wherein the calculationunit is configured to calculate the movement information of thereference point set on the periphery side with respect to the referencepoint set on the target-site side, between the medical image in whichthe setting unit sets the reference points and a medical imageregistered by the registration unit with respect to that medical image.8. The medical image processing apparatus according to claim 7, whereinthe registration unit is configured to perform deformation registrationthat maintains a normal structure of a target site in a medical image.9. The medical image processing apparatus according to claim 7, whereinregistration unit is configured to perform registration between medicalimages that are targets for registration, after correcting the medicalimages that are the targets for registration in accordance with an imagecondition corresponding to a position at which the setting unit sets thereference points.
 10. The medical image processing apparatus accordingto claim 9, wherein the image condition differs as between the positionof the reference point of the target-site side and the position of thereference point of the periphery side of the target site.
 11. Themedical image processing apparatus according to claim 5, wherein thecalculation unit is configured to correct slippage obtained for eachposition in the target site or for each position on a surface of thetarget site by using a correction coefficient set for each position inthe target site or for each position on the surface of the target site.12. The medical image processing apparatus according to claim 5, whereinthe medical image is captured by an X-ray 4D-CT apparatus, the targetsite is a lung, and the calculation unit is configured to calculate theslippage of a pleura.
 13. The medical image processing apparatusaccording to claim 1, further comprising a unit configured to acquire anexclusion region that is a region in the medical image in which areference point is not set, wherein the setting unit is configured toset the reference point outside the exclusion region in the medicalimage.
 14. A medical image processing apparatus comprising: anacquisition unit configured to acquire plural pieces of medical imagedata in time phases; an extraction unit configured to extract a targetsite with respect to at least one piece of the plural pieces of medicalimage data acquired in accordance with the acquisition unit; a settingunit configured to respectively set a reference point on an outline ofthe target site extracted by the extraction unit, and set a referencepoint on either a target-site side or a periphery side of the targetsite; and a movement information calculation unit configured tocalculate movement information for the reference points set by thesetting unit.
 15. A medical image processing method comprising:acquiring a plurality of medical images in time phases; extracting atarget site from at least one medical image from the plurality ofmedical images; setting a reference point on each of a target-site side,and a periphery side of the target site based on an outline of thetarget site extracted in the extracting; and calculating movementinformation for the reference points set in the setting, wherein thesetting includes setting a plurality of pairs of a first reference pointon the target-site side and a second reference point on the peripheryside, and wherein the calculating includes calculating the movementinformation of the second reference point with respect to the firstreference point.
 16. A medical image processing method comprising:acquiring plural pieces of medical image data in time phases; extractinga target site with respect to at least one piece of the plural pieces ofmedical image data acquired in accordance with the acquiring;respectively setting a reference point on an outline of the target siteextracted in the extracting, and setting a reference point on either atarget-site side or a periphery side of the target site; and calculatingmovement information for the reference points set in the setting.
 17. Anon-transitory computer-readable storage medium storing a computerprogram for causing a computer to function as: an acquisition unitconfigured to acquire a plurality of medical images in time phases; anextraction unit configured to extract a target site from at least onemedical image from the plurality of medical images; a setting unitconfigured to set a reference point on each of a target-site side, and aperiphery side of the target site based on an outline of the target siteextracted by the extraction unit; and a calculation unit configured tocalculate movement information for the reference points set by thesetting unit, wherein the setting unit is configured to set a pluralityof pairs of a first reference point on the target-site side and a secondreference point on the periphery side, and wherein the calculation unitis configured to calculate the movement information of the secondreference point with respect to the first reference point.
 18. Themedical image processing apparatus according to claim 1, wherein thefirst reference point and the second reference point are across fromeach other over the outline of the target site.
 19. A medical imageprocessing apparatus comprising: an image acquisition unit configured toacquire a plurality of medical images captured at different temporalpoints and at different respiratory conditions of a patient; anextraction unit configured to extract a lung field region from at leastone medical image from the plurality of medical images; an informationacquisition unit configured to acquire a slippage of pleura by comparinga movement amount of the lung field region and a movement amount of anoutside region of the lung field region; and a display processing unitconfigured to visualize the slippage of pleura on at least one medicalimage from the plurality of medical images.